WO2002095959A2 - A control feedback system and method for bulk material industrial processes using automated object or particle analysis - Google Patents
A control feedback system and method for bulk material industrial processes using automated object or particle analysis Download PDFInfo
- Publication number
- WO2002095959A2 WO2002095959A2 PCT/US2002/018560 US0218560W WO02095959A2 WO 2002095959 A2 WO2002095959 A2 WO 2002095959A2 US 0218560 W US0218560 W US 0218560W WO 02095959 A2 WO02095959 A2 WO 02095959A2
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- sample
- control system
- particles
- definition
- process control
- Prior art date
Links
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B15/00—Systems controlled by a computer
- G05B15/02—Systems controlled by a computer electric
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B02—CRUSHING, PULVERISING, OR DISINTEGRATING; PREPARATORY TREATMENT OF GRAIN FOR MILLING
- B02C—CRUSHING, PULVERISING, OR DISINTEGRATING IN GENERAL; MILLING GRAIN
- B02C25/00—Control arrangements specially adapted for crushing or disintegrating
Definitions
- the present invention relates to industrial processes wherein streams of irregularly shaped objects or particles of bulk materials are processed from a raw state into a finished product state or simply transferred along a conveyor belt.
- the present invention relates to industrial processes using automated object or particle analysis as part of the industrial process.
- One typical prior art method for providing size distribution measurements of bulk material moving on a conveyor involves using an automated or manual sampling procedure. This prior art method involves analyzing a physical sample of the conveyed raw material in a laboratory setting where screen sieve analysis is used to determine the size of particles in the material sample.
- screen sieve analysis is used to determine the size of particles in the material sample.
- conventional techniques for physically characterizing the size and shape or reflectance of materials traveling on a conveyor in an industrial process. These conventional techniques, which are used primarily for sorting operations, employ a variety of different techniques.
- U.S. Patent No. 3,357,557 discloses a technique for using reflected light as a means of determining the flatness of semiconductor chips.
- Various conventional automated particle analysis systems are commercially available for rapidly determining the grain size distribution of unbound aggregates. These conventional systems provide a faster alternative to standard sieve analysis. These conventional machines capture and analyze digital images of the aggregate particles on a conveyor stream to determine size gradation.
- Such conventional particle analysis systems include, for example, the VDG-40 Video Grader developed by Emaco, Ltd. of Canada; the Computer Particle Analyzer (CPA) developed by W.F. Tyler and Terry Reckart; the OptiSizer, PFDA5400, by Micromeritics Instrument Corp.; Video Imaging System (VIS), by John B. Long Company; Particle Size Distribution Analyzer (PSDA), by Buffalo Wire Works Company; and the Particle Parameter Measurement System (PPMS), by Scientific Industrial Automation Pty.
- VDG-40 Video Grader developed by Emaco, Ltd. of Canada
- CPA Computer Particle Analyzer
- OptiSizer PFDA5400
- VIS Video Imaging System
- PSDA Particle Size Distribution Analyzer
- PPMS Particle
- a control feedback system and method for industrial processes using automated particle or object analysis includes a particle characteristic measuring unit to obtain measured characteristics of a sample; an optimal characteristic definition for comparison with the measured characteristics; a corrective action database for defining and selecting actions to be taken in response to a comparison of the measured characteristics with the optimal characteristic definition; and a control line network to transfer control signals to a plurality of processing units in response to a selected action to be taken.
- Figure 1 illustrates a design for a particle parameter measurement system.
- Figure 2 illustrates a block diagram of an industrial process system using the present invention.
- Figure 3 illustrates an improved design for a particle parameter measurement system wherein temperature and moisture are measured.
- Figure 4 illustrates an improved design for a particle parameter measurement system wherein texture, reflectivity, color, and opacity are measured.
- Figure 5 illustrates an improved design for a particle parameter measurement system wherein chemical composition is measured.
- Figure 6 illustrates a block diagram of an alternative embodiment of the industrial process system using the present invention.
- the present invention is a control feedback system and method for industrial processes using automated particle or object analysis.
- numerous specific details are set forth in order to provide a thorough understanding of the present invention. However, it will be apparent to one of ordinary skill in the art that these specific details need not be used to practice the present invention. In other circumstances, well-known structures, materials, circuits, processes, and interfaces have not been shown or described in detail in order not to unnecessarily obscure the present invention.
- FIG. 1 one example of a conventional automatic particle measurement system is illustrated.
- a main conveyor 1 is shown carrying particulate material.
- a primary sampling device 2 is provided to divert a pre-selected amount of the particulate material from the main conveyor 1 into a hopper 3.
- the pre-selected sample must be a truly representative sample and not unevenly distributed or misrepresentative of the raw material. Normally, this is done by taking a complete cross-section of the material on the conveyor belt using a cross-belt sampler or taking a complete sample from the end of the belt. The material is withdrawn from the hopper by a vibrating feeder 4.
- the vibrating feeder 4 is a conventional design with an adjustable vibration rate and/or vibration amplitude and/or inclination to provide for a varying rate of throughput or speed.
- vibrating feeder 4 can be comprised of a plurality of separate individual vibrating feeders each of which can be used to vary the distribution and rate of material dropping off the end of the vibrating feeder 4. It will be apparent to those of ordinary skill in the art that some other conventional device could separate the particles into an approximate monolayer and keep particle overlap to a minimum.
- the vibrating feeder 4 is adjusted to optimally distribute particulate material so that it discharges off the end of vibrating feeder 4 in an approximate monolayer.
- a camera imaging region or measurement window 5 is provided and has backlighting provided by a light box 6.
- the light box 6 and camera 7 are surrounded by environmental enclosure 8 to protect the arrangement from environmental dust and to exclude extraneous external light from entering the environment.
- the environmental housing is protected from ingress of dust by either positive pressure or by suction.
- pneumatic wipers (not shown) can be provided to clean the surface of backlight 6 and the camera window 7.
- the arrangement illustrated in Figure 1 causes a sample of particulate material to drop off the end of vibrating feeder 4 into the camera-imaging region 5 and subsequently onto conveyor 11 , which returns the sample to the industrial process.
- light box 6 illuminates the particles in the sample for imaging by camera 7.
- the present invention includes built-in protection to eliminate counting particles more than once as they fall through the camera-imaging region 5. This is done by putting in a minimum time between images based on height of the vibrating feeder 4 above imaging region 5 and the bottom of the image taken within the image region 5. Clearly, this minimum time is dependent on gravitational acceleration.
- camera 7 captures static images of the falling particles.
- processing logic embodied within processor 9 and coupled via control lines 10, the system of Figure 1 can compute various characteristics, such as size and shape, from the images captured by camera 7.
- characteristics such as size and shape
- connection 10 between the enclosure 8 and processing system 9 is by way of an optical fiber link.
- This link allows communication over distances of up to 2 kilometers and overcomes difficulties associated with electrical interference. This arrangement also eliminates earth loops and different earth potential influences on the video signal.
- the software associated with processing system 9 is able to detect any overlapping particles and reject them for the purposes of the measurement and size distribution.
- Camera 7 is typically a CCD (charge coupled device) camera using an electronic shutter controlled by a computer to freeze the image and transfer the image to a frame buffer associated with processing system 9.
- CCD charge coupled device
- FIG. 2 a block diagram illustrates one embodiment of an industrial process system of the present invention.
- Figure 2 illustrates an improved particle measurement system denoted the advanced vision particle measurement system (AVPM) 100, a simplified embodiment of which was illustrated in Figure 1 and described above, in the context of an overall industrial system 50.
- AVPM advanced vision particle measurement system
- AVPM 100 monitors various characteristics of objects and/or materials being transported on conveyor 119.
- the AVPM could also monitor conveyors 111,113,115 and 117 (See Figure 6). This arrangement would enable monitoring of the raw materials and the performance of the raw processing unit 118.
- AVPM 100 monitors characteristics including the size, shape, and computed volume and weight of objects or materials on conveyor 119.
- processor 9 of AVPM 100 In a memory or data storage area of processor 9 of AVPM 100, a set of information 101 describing a desired or optimal set of object or material characteristics on conveyor 119 is stored. This optimal characteristic data set
- the optimal characteristic definition 101 is provided to and maintained by processor 9 of
- AVPM 100 In operation as described above, AVPM 100 periodically takes samples from the objects or materials traveling on conveyor 119. These samples are analyzed as described above to obtain measurements for each of the prescribed characteristics of the objects or materials on conveyor 119. After each sample is obtained and the corresponding characteristics of the sample are measured, the measured sample characteristics are compared with the optimal characteristic definition 101. As a result of this comparison, it may be determined that the characteristics of the measured sample deviate from the characteristics defined by the optimal characteristic definition
- processor 9 can use rules based logic or a corrective action database 103 to determine an action to take to reduce the deviation found between the characteristics of a measured sample and the characteristics defined in the optimal characteristic definition 101.
- various corrective actions may be predefined in the rules based logic or corrective action database 103.
- the AVPM 100 may have determined that the average size of a measured sample taken from objects or materials on conveyor 119 may be larger than the average size defined in the optimal characteristic definition 101. As a result of this size deviation, processor 9 will determine that the average size of subsequent measured samples must be reduced.
- Processor 9 in AVPM 100 accesses corrective action database 103 to obtain an appropriate corrective action to take to reduce the average size of subsequent measured samples.
- This corrective action database 103 contains predefined sets of corrective actions necessary to handle various deviations of the measurements of characteristics of measured samples as compared with the optimal characteristic definition 101.
- the corrective action database 103 may define a corrective action for reducing the average size of subsequent measured samples to be configuring raw processing unit 118 to crush raw material to a finer granularity or causing raw processing unit 118 to process raw material for a longer period of time thereby producing smaller size material.
- Either of these corrective actions or other corrective actions defined in corrective action database 103 may be obtained by processor 9 in response to finding a deviation between a measured sample and the optimal characteristic definition 101.
- AVPM 100 measures characteristics of samples obtained from objects or materials on conveyor 119 and determines corrective actions necessary to reduce the deviation of the measured characteristics of the samples as compared with the optimal characteristic definition 101.
- corrective actions defined in corrective action database 103 can be numerous depending upon the characteristics being measured by AVPM 100 and the various processing units available in a particular industrial system, such as the sample industrial system 50 shown in Figure 2.
- AVPM 100 determines which corrective action is necessary to cause a measured sample to conform to the optimal characteristic definition 101
- AVPM 100 generates various signals on a control line network including line 132, illustrated in Figure 2, to configure and control other units within the industrial system 50 for the purpose of causing the characteristics of the measured sample on conveyor 119 to conform with the optimal characteristic definition 101.
- the control line network including line 132 between the AVPM 100 and other processing units within the industrial system 50 is by way of an optical fiber link. This link allows communication over distances of up to 2 kilometers and overcomes difficulties associated with electrical and environmental interference. This arrangement also eliminates earth loops and different earth potential influences on the control signals.
- AVPM 100 After accessing corrective action database 103, determines that raw processing unit 118 must be configured to reduce the mean size of the material it is processing. Thus, AVPM 100 generates a signal on line
- AVPM 100 via a signal on line 132, may program raw processing unit 118 to either process the raw material for a greater length of time thereby reducing the average size of material output on conveyor 119 or alternatively raw processing unit 118 can be programmed by AVPM 100 to change various control dimensions within the crusher to produce smaller size output.
- AVPM 100 can also take other corrective actions as predefined in corrective action database 103 to conform measured characteristics of material on conveyor 119 to optimal characteristic definition 101.
- each of the raw material sources 110-114 provide their output to accumulator
- the raw material sources 110-114 may be loaded initially with raw materials having various known characteristics.
- raw material source A 110 can be initially loaded with a type of material having a relatively small average size.
- Raw material source B 112 could be initially loaded with a type of material having an average relative size slightly larger than the size of material loaded in raw material source A 110.
- raw material source N 114 can be initially loaded with material having an average relative size slightly larger than both raw material source A 110 and raw material source B 112. In this manner, a range of relative sizes of raw material can be spread over a number of independent raw material sources 110-114.
- AVPM 100 can control the size characteristics of raw material measured on conveyor 119 by controlling the level of output being provided by each of the raw material sources 110-114. For example, again referring to the example set forth above related to the average size of material on conveyor 119, AVPM 100 can take an alternative corrective action as defined in the corrective action database 103 to cause the characteristics of the measured sample to conform to the optimal characteristic definition 101. In this example, AVPM 100 sends a signal on line 132 to control the output of each of the plurality of raw material sources
- AVPM 100 can adjust the output provided by each of the raw material sources 110-114 to adjust the characteristics of the raw material to a desired characteristic level provided within the range of characteristics available across each of the raw material sources 110-114. For example, if the measured sample on conveyor on 119 is determined to be larger in average size than the desired optimal characteristic definition 101, AVPM 100 sends a signal on line 132 to raw material source 110 on line 134 to cause raw material source
- a 110 to increase its output of small raw material provided to accumulator 116 on conveyor 111.
- AVPM 100 also sends a control signal to raw material source
- 110-114 will be a smaller average size.
- the smaller average size raw material collected by accumulator 116 will be transferred to raw processing unit 118 via conveyor 117. Because the average size of raw material provided to raw processing unit 116 will be initially smaller, the output of raw material from raw processing unit
- the AVPM 100 can also be coupled to conveyors 111, 113, 115, and 117 (See Figure 6). Using the techniques described above, the AVPM 100 can monitor the characteristics of material on conveyors 111, 113, 115, and 117 to obtain information on size distribution and the other parameters of each type of raw material. This could be useful in determining the contribution of each type of raw material in the overlapping size ranges.
- AVPM 100 can also produce corrective actions and control signals on line 132 for the purpose of controlling a variety of characteristics of objects or materials measured on conveyor 119.
- AVPM 100 can monitor and control various characteristics of objects or materials being processed in industrial system 50. These characteristics monitored and controlled by AVPM 100 could include the size, shape, volume, weight, density, temperature, moisture content, texture, reflectivity, color, opacity, and chemical composition of materials transferred on conveyor 119.
- AVPM 100 also retains a predefined optimal characteristic definition 101 for each of the characteristics enumerated above. As such, a predefined profile of a desired optimal set of output material characteristics can be defined in the optimal characteristic definition 101.
- material characteristics such as size, shape, volume, density and weight can be measured.
- the size and shape of particles within a measured sample can be determined.
- the volume of each of the particles of a measured sample and thus the average volume for the sample can be inferred from the size and shape determined from the sample images.
- volume of particles in a particular sample is based on the minimum and maximum radii of the best fit ellipse of the 2-dimensional projected image of the particle as illuminated by back light 6 onto camera 7 via the camera lens.
- the formula for determining the volume is provided as 4/ 3a b ⁇ F, where a is the minimum ellipse radius, b is the maximum ellipse radius and F is a compensation correction based on shape and other known variables that influence the results.
- the weight of a measured sample can be determined per measured particle as inferred from the volume of particular particles, the known type of material, and or the known material density after excluding overlapping portions of the particle images captured by camera 7. Thus, weight can be estimated using the predetermined volume in combination with a material density. Given the weight per measured particle, the average weight of a particular sample can also be determined.
- These measured characteristics of a material sample can be used as described above to cause various corrective actions in the industrial process to conform to the measured characteristics to the desired optimal set of characteristics. Using an improved AVPM system as described below, additional characteristics including temperature and moisture, texture, reflectivity, color, and opacity, and chemical composition can be monitored and used as control inputs for an industrial process.
- the present invention also measures temperature and moisture of objects or materials traveling through industrial process 50.
- an improved AVPM 100 system including temperature and moisture unit 106 is illustrated. Temperature and moisture unit 106 is used to measure the temperature and moisture content characteristics of a sample dropping through region 5.
- temperature and moisture unit 106 includes infrared detectors for receiving temperature information of sample particles passing through region 5. It will be apparent to one of ordinary skill in the art that these infrared detectors are appropriately shielded from any interference from the light of light box 6. Using the infrared detectors, a level of infrared energy emitted or reflected by sample particles dropping through region 5 can be detected and transferred to processor 9 for further processing.
- Temperature and moisture unit 106 also includes a conventional moisture meter such as the Micro-Moist LB 354 unit, which is conventionally available. This conventional unit uses microwave techniques, which causes rotation of unbound water molecules in particles of a sample dropping through region 5. The resulting phase shift serves as a direct measure of the moisture content of particles of the sample.
- the moisture content characteristics of the sample can be measured by temperature and moisture unit 106 and transferred to processor 9 for further processing. Once the temperature and moisture characteristics for the measured sample are obtained using temperature and moisture unit 106, the processor 9 retains these temperature and moisture characteristics for the measured sample. In the manner described above, the measured temperature and moisture characteristics are compared with the optimal characteristic definition 101 to determine if a deviation between the measured characteristics and the desired characteristics is present.
- AVPM 100 accesses the corrective action database 103 to obtain a corrective action for eliminating the temperature and/or moisture deviation.
- AVPM 100 can transmit signals on line 132 of the control line network connected to various processing units of industrial process 50 to cause an increase or decrease in temperature and/or moisture content of subsequent measured samples.
- AVPM 100 can cause a variation in the mix of raw materials provided from various raw material sources 110-
- AVPM 100 can signal accumulator 116 to add or remove moisture from the accumulated material.
- AVPM 100 can also signal accumulator 116 to increase or decrease a level of heat or cooling applied to the accumulated raw materials.
- AVPM 100 uses temperature and moisture characteristics of a measured sample to configure and control the operation of the industrial process.
- the present invention can also measure the texture, reflectivity, color, and opacity characteristics of objects or materials traveling through an industrial process.
- an improved AVPM 100 which includes, texture, reflectivity, color, and opacity unit 107.
- Unit 107 measures the texture, reflectivity, color, and opacity of particles of a measured sample passing through region 5.
- a conventional laser is used to illuminate particles of a sample passing through region 5. It will be apparent to one of ordinary skill in the art that the laser emitters are properly shielded from interference from the light of light box 6. Using the laser illumination of particles in region 5, estimates of texture, reflectivity, and opacity for particular sample particles can be made and transferred to processor 9.
- unit 107 may include various color light sources for illuminating particles of the measured sample in various colors.
- AVPM 100 can access the corrective action database 103 to determine a corrective action necessary in the industrial system to cause the texture, reflectivity, color, and opacity characteristics of the measured sample to conform to the optimal characteristic definition 101.
- AVPM 100 can produce a signal on line 132 to cause a variation in the mix of raw material provided by raw material sources 110-114.
- This variation in raw material sources triggered by AVPM 100 can be used to configure the characteristics of the raw materials accumulated by accumulator 116. In this manner, raw materials with the desired texture, reflectivity, color, and opacity can be collected in accumulator 116 and provided to subsequent processing units of the industrial process 50.
- the present invention also measures the chemical composition characteristics of objects or materials traveling through an industrial process.
- an improved AVPM 100 is shown including a chemical composition unit
- Unit 108 is used to measure the chemical composition of particles in the sample falling through region 5.
- Conventional techniques are known for measuring the chemical composition of materials in real-time.
- one such real-time chemical composition measuring system is manufactured by Gamma-Metrics of
- AVPM 100 system illustrated in Figure 5 is used to capture chemical composition characteristics for the measured sample. Again, using the technique described above, the chemical composition characteristics of the measured sample are compared against the optimal characteristic definition 101 to determine if there is a deviation. If so,
- AVPM 100 accesses the corrective action database 103 to configure and control processing units of industrial process 50 to reduce the deviation.
- AVPM AVPM
- Raw material sources 110-114 may initially be loaded with raw material having a range of chemical compositions.
- AVPM 100 can control the chemical composition of the combined raw material collected in accumulator 116.
- AVPM 100 can control the chemical composition of objects or materials provided to subsequent processing units in industrial process 50. It will be apparent to one of ordinary skill in the art that additional characteristics of a measured sample may similarly be measured by a AVPM system and these characteristics used by AVPM 100 to configure and control the flow of material through a particular industrial process.
- AVPM 100 can also use additional information to control the industrial process 50.
- AVPM 100 can use economic or business information such as unit cost information, demographics, or sales criteria to configure the objects or materials produced by finished processing unit 120.
- economic or business information such as unit cost information, demographics, or sales criteria to configure the objects or materials produced by finished processing unit 120.
- AVPM 100 can adjust the set quantity or configuration of finished products produced by finished processing unit 120.
- AVPM 100 makes these adjustments based on a comparison between the economic or business information and the optimal characteristic definition 101. In this manner, the products produced by finished processing unit 120 will conform to a predefined set of economic or business criteria.
- the additional information used by AVPM 100 may include information other than economic or business information.
Abstract
Description
Claims
Priority Applications (3)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
EP02737470A EP1402452A4 (en) | 2001-05-18 | 2002-05-08 | A control feedback system and method for bulk material industrial processes using automated object or particle analysis |
NZ529760A NZ529760A (en) | 2001-05-18 | 2002-05-08 | A control feedback system and method for bulk material industrial processes using automated object or particle analysis |
NO20035100A NO20035100D0 (en) | 2001-05-18 | 2003-11-17 | Feedback method and system with feedback, for industrial processes on bulk material and with the use of automatic object or particle analysis |
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US09/860,866 | 2001-05-18 | ||
US09/860,866 US6629010B2 (en) | 2001-05-18 | 2001-05-18 | Control feedback system and method for bulk material industrial processes using automated object or particle analysis |
Publications (2)
Publication Number | Publication Date |
---|---|
WO2002095959A2 true WO2002095959A2 (en) | 2002-11-28 |
WO2002095959A3 WO2002095959A3 (en) | 2003-07-31 |
Family
ID=25334222
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
PCT/US2002/018560 WO2002095959A2 (en) | 2001-05-18 | 2002-05-08 | A control feedback system and method for bulk material industrial processes using automated object or particle analysis |
Country Status (6)
Country | Link |
---|---|
US (1) | US6629010B2 (en) |
EP (1) | EP1402452A4 (en) |
CN (1) | CN1509453A (en) |
NO (1) | NO20035100D0 (en) |
NZ (1) | NZ529760A (en) |
WO (1) | WO2002095959A2 (en) |
Families Citing this family (27)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US6885904B2 (en) * | 2001-05-18 | 2005-04-26 | Advanced Vision Particle Measurement, Inc. | Control feedback system and method for bulk material industrial processes using automated object or particle analysis |
US6675073B2 (en) * | 2001-11-20 | 2004-01-06 | Steve Kieman | System and method for tuning the weight control of a flow of material |
US7660440B2 (en) * | 2002-11-07 | 2010-02-09 | Frito-Lay North America, Inc. | Method for on-line machine vision measurement, monitoring and control of organoleptic properties of products for on-line manufacturing processes |
US7009703B2 (en) * | 2003-03-27 | 2006-03-07 | J.M.Canty Inc. | Granular product inspection device |
US7077311B1 (en) * | 2003-10-29 | 2006-07-18 | Banctec, Inc. | Document transport control system |
US20050097021A1 (en) * | 2003-11-03 | 2005-05-05 | Martin Behr | Object analysis apparatus |
US20090206286A1 (en) * | 2004-06-25 | 2009-08-20 | Dario Pierri | System and method for particle stream characterization |
DE102004031052A1 (en) * | 2004-06-25 | 2006-01-12 | Bühler AG | System and process for grinding material characterization in a roller mill |
WO2006116882A1 (en) * | 2005-05-02 | 2006-11-09 | Bühler AG | System and method for characterisation of a particle flow |
US8620059B2 (en) * | 2007-12-13 | 2013-12-31 | Fpinnovations | Characterizing wood furnish by edge pixelated imaging |
DE102008001749A1 (en) | 2008-05-14 | 2009-11-19 | Bühler AG | System and process for the grinding stock characterization in a grinding plant |
UA106632C2 (en) * | 2009-09-07 | 2014-09-25 | Кертін Юніверсеті Оф Текноледжі | METHOD OF Sorting Bulk |
IT1401710B1 (en) * | 2010-06-17 | 2013-08-02 | Bies Srl | UNIT FOR THE PRODUCTION CONTROL OF THE INERT IN A CABLE AND ITS METHOD |
CN102252714A (en) * | 2011-06-27 | 2011-11-23 | 南通北极光自动控制技术有限公司 | On-line solid physical optical characteristic analysis system |
US20150021465A1 (en) | 2013-07-16 | 2015-01-22 | Leeo, Inc. | Electronic device with environmental monitoring |
US9116137B1 (en) | 2014-07-15 | 2015-08-25 | Leeo, Inc. | Selective electrical coupling based on environmental conditions |
US9372477B2 (en) | 2014-07-15 | 2016-06-21 | Leeo, Inc. | Selective electrical coupling based on environmental conditions |
US9092060B1 (en) | 2014-08-27 | 2015-07-28 | Leeo, Inc. | Intuitive thermal user interface |
US10304123B2 (en) | 2014-09-08 | 2019-05-28 | Leeo, Inc. | Environmental monitoring device with event-driven service |
US9445451B2 (en) | 2014-10-20 | 2016-09-13 | Leeo, Inc. | Communicating arbitrary attributes using a predefined characteristic |
US10026304B2 (en) | 2014-10-20 | 2018-07-17 | Leeo, Inc. | Calibrating an environmental monitoring device |
US10805775B2 (en) | 2015-11-06 | 2020-10-13 | Jon Castor | Electronic-device detection and activity association |
US9801013B2 (en) | 2015-11-06 | 2017-10-24 | Leeo, Inc. | Electronic-device association based on location duration |
FI20155908A (en) * | 2015-12-01 | 2017-06-02 | Outotec Finland Oy | Process and arrangement for controlling a atomization process comprising a grinding circuit |
FI20155909A (en) * | 2015-12-01 | 2017-06-02 | Outotec Finland Oy | Method and arrangement for controlling the comminution process |
GB2559964A (en) * | 2017-02-16 | 2018-08-29 | Her Majesty In Right Of Canada As Represented By The Mini Of Natural Resources | Methods for measuring properties of rock pieces |
IT201700023354A1 (en) * | 2017-03-02 | 2018-09-02 | Cams Srl | A METHOD OF CONTROL OF AN ELEMENT TREATMENT PLANT TO BE RECYCLED OR DISPOSED AND PLANT FOR THE TREATMENT OF ELEMENTS TO BE RECYCLED OR DISPOSED OF |
Citations (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US4205384A (en) * | 1977-09-14 | 1980-05-27 | Wibau Gmbh | Method for the analytic determination of physical characteristics of a material |
US4295200A (en) * | 1979-11-02 | 1981-10-13 | The United States Of America As Represented By The Secretary Of The Navy | Automatic particle analyzing system |
US5011285A (en) * | 1987-12-18 | 1991-04-30 | Norsk Hydro A.S. | Method and apparatus for performing automatic particle analysis |
US5157976A (en) * | 1990-07-27 | 1992-10-27 | Hajime Industries Ltd. | Powder granule sample inspection apparatus |
US5303310A (en) * | 1991-08-30 | 1994-04-12 | Imc Fertilizer, Inc. | Method and apparatus for image analysis of composite ores |
US5519793A (en) * | 1992-11-05 | 1996-05-21 | The United States Of America As Represented By The Secretary Of The Interior | Apparatus and method for computer vision measurements |
WO1997014950A1 (en) * | 1995-10-16 | 1997-04-24 | Scientific Industrial Automation Pty. Limited | Method and apparatus for sizing particulate material |
US6535769B1 (en) * | 1999-03-12 | 2003-03-18 | Sony Electronics Pte Ltd. | Monitoring system for monitoring processing equipment |
Family Cites Families (35)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US3097744A (en) | 1961-02-27 | 1963-07-16 | K & H Equipment Ltd | Quantitative photometric materials sorter |
US3357557A (en) | 1965-07-30 | 1967-12-12 | Affiliated Mfg Corp | Radiant energy method and apparatus of determining physical characteristics |
GB1152407A (en) | 1968-02-02 | 1969-05-21 | Sphere Invest Ltd | Photometric Sorting Apparatus |
GB1393061A (en) | 1973-03-22 | 1975-05-07 | Sphere Invest | Integrated reflectance photometric sorter |
US4131668A (en) * | 1974-03-15 | 1978-12-26 | Nippon Steel Corporation | Iron ore pellet process control |
US4057146A (en) | 1974-05-24 | 1977-11-08 | Xeltron, S.A. | Optical sorting apparatus |
US3977526A (en) | 1975-06-27 | 1976-08-31 | Sphere Investments Limited | Tracking systems for sorting apparatus |
US4122952A (en) | 1976-04-26 | 1978-10-31 | Sphere Investments Limited | Photometric sorters |
US4236640A (en) | 1978-12-21 | 1980-12-02 | The Superior Oil Company | Separation of nahcolite from oil shale by infrared sorting |
US4251475A (en) * | 1978-12-29 | 1981-02-17 | Owens-Corning Fiberglas Corporation | Method and apparatus for controlling the proportion of liquid and dry particulate matter added to a pelletizer |
DE2929430C2 (en) * | 1979-07-20 | 1981-10-01 | Stahlwerke Peine-Salzgitter Ag, 3150 Peine | Method and device for analyzing the solids content in a hydraulic conveying flow made up of solid particles and a carrier liquid |
US4348277A (en) | 1979-11-06 | 1982-09-07 | Lockwood Graders (Uk) Limited | Article sorting apparatus and method |
DE3015665C2 (en) | 1980-04-23 | 1982-07-22 | Gebr. Schmidt, 8432 Beilngries | Sorting device |
JPS5987081A (en) | 1982-11-09 | 1984-05-19 | 池上通信機株式会社 | Inspection system of external appearance and quality |
US4624367A (en) | 1984-04-20 | 1986-11-25 | Shafer John L | Method and apparatus for determining conformity of a predetermined shape related characteristics of an object or stream of objects by shape analysis |
EP0363828B1 (en) | 1988-10-11 | 1999-01-07 | Kabushiki Kaisha Ouyo Keisoku Kenkyusho | Method and apparatus for adaptive learning type general purpose image measurement and recognition |
NL8901380A (en) | 1989-02-14 | 1990-09-03 | Heuft Qualiplus Bv | SIMULTANEOUS DOUBLE INSPECTION. |
US5060290A (en) | 1989-09-05 | 1991-10-22 | Dole Dried Fruit And Nut Company | Algorithm for gray scale analysis especially of fruit or nuts |
DE4119240A1 (en) | 1991-06-07 | 1992-12-10 | Matthias Dipl Ing Schumann | METHOD FOR DETERMINING THE PARTICLE SIZE DISTRIBUTION OF PARTICLE MIXTURES |
JPH07500182A (en) | 1991-10-01 | 1995-01-05 | オセニー リミテッド | Scattered/transmitted light information system |
FR2697086B1 (en) | 1992-10-20 | 1994-12-09 | Thomson Csf | Method and device for inspecting transparent material. |
GB2273154B (en) | 1992-12-02 | 1996-12-11 | Buehler Ag | Method for cleaning and sorting bulk material |
ZA943378B (en) * | 1993-05-26 | 1995-01-16 | De Beers Ind Diamond | Classification based on thermal properties |
US5577733A (en) | 1994-04-08 | 1996-11-26 | Downing; Dennis L. | Targeting system |
US5754677A (en) | 1994-10-25 | 1998-05-19 | Fuji Machine Mfg. Co., Ltd. | Image processing apparatus |
US5732147A (en) | 1995-06-07 | 1998-03-24 | Agri-Tech, Inc. | Defective object inspection and separation system using image analysis and curvature transformation |
WO1997032181A1 (en) | 1996-03-01 | 1997-09-04 | Durand-Wayland, Inc. | Optical inspection apparatus and method for articles |
JP2916893B2 (en) * | 1996-07-05 | 1999-07-05 | 株式会社日立製作所 | Waste treatment apparatus and control method |
US6112588A (en) | 1996-10-25 | 2000-09-05 | Speedline Technologies, Inc. | Method and apparatus for measuring the size of drops of a viscous material dispensed from a dispensing system |
US6112903A (en) | 1997-08-20 | 2000-09-05 | Eftek Corporation | Cullet sorting by differential thermal characteristics |
US6067155A (en) | 1997-12-24 | 2000-05-23 | Owens-Brockway Glass Container Inc. | Optical inspection of transparent containers using infrared and polarized visible light |
US6049379A (en) | 1997-12-30 | 2000-04-11 | Coors Brewing Company | Method for inspecting translucent objects using imaging techniques |
US6061125A (en) | 1998-01-27 | 2000-05-09 | Insight Control Systems International | Dual illumination apparatus for container inspection |
US5969810A (en) | 1998-05-14 | 1999-10-19 | Owens-Brockway Glass Container Inc. | Optical inspection of transparent containers using two cameras and a single light source |
WO2001003841A1 (en) * | 1999-07-08 | 2001-01-18 | Imeco Automazioni S.R.L. | System and self-moving device for the control of milling processes |
-
2001
- 2001-05-18 US US09/860,866 patent/US6629010B2/en not_active Expired - Lifetime
-
2002
- 2002-05-08 CN CNA028101685A patent/CN1509453A/en active Pending
- 2002-05-08 WO PCT/US2002/018560 patent/WO2002095959A2/en not_active Application Discontinuation
- 2002-05-08 EP EP02737470A patent/EP1402452A4/en not_active Withdrawn
- 2002-05-08 NZ NZ529760A patent/NZ529760A/en unknown
-
2003
- 2003-11-17 NO NO20035100A patent/NO20035100D0/en not_active Application Discontinuation
Patent Citations (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US4205384A (en) * | 1977-09-14 | 1980-05-27 | Wibau Gmbh | Method for the analytic determination of physical characteristics of a material |
US4295200A (en) * | 1979-11-02 | 1981-10-13 | The United States Of America As Represented By The Secretary Of The Navy | Automatic particle analyzing system |
US5011285A (en) * | 1987-12-18 | 1991-04-30 | Norsk Hydro A.S. | Method and apparatus for performing automatic particle analysis |
US5157976A (en) * | 1990-07-27 | 1992-10-27 | Hajime Industries Ltd. | Powder granule sample inspection apparatus |
US5303310A (en) * | 1991-08-30 | 1994-04-12 | Imc Fertilizer, Inc. | Method and apparatus for image analysis of composite ores |
US5519793A (en) * | 1992-11-05 | 1996-05-21 | The United States Of America As Represented By The Secretary Of The Interior | Apparatus and method for computer vision measurements |
WO1997014950A1 (en) * | 1995-10-16 | 1997-04-24 | Scientific Industrial Automation Pty. Limited | Method and apparatus for sizing particulate material |
US6535769B1 (en) * | 1999-03-12 | 2003-03-18 | Sony Electronics Pte Ltd. | Monitoring system for monitoring processing equipment |
Non-Patent Citations (1)
Title |
---|
See also references of EP1402452A2 * |
Also Published As
Publication number | Publication date |
---|---|
EP1402452A4 (en) | 2005-06-29 |
US20020170367A1 (en) | 2002-11-21 |
WO2002095959A3 (en) | 2003-07-31 |
US6629010B2 (en) | 2003-09-30 |
NZ529760A (en) | 2007-06-29 |
EP1402452A2 (en) | 2004-03-31 |
NO20035100D0 (en) | 2003-11-17 |
CN1509453A (en) | 2004-06-30 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
US6629010B2 (en) | Control feedback system and method for bulk material industrial processes using automated object or particle analysis | |
US6885904B2 (en) | Control feedback system and method for bulk material industrial processes using automated object or particle analysis | |
US5917927A (en) | Grain inspection and analysis apparatus and method | |
CN110476053B (en) | Raw material particle size distribution measuring device, particle size distribution measuring method, and porosity measuring device | |
CA2647721C (en) | Device and method for the flexible classification of polycrystalline silicon fragments | |
US8233667B2 (en) | Apparatus and method for analysis of size, form and angularity and for compositional analysis of mineral and rock particles | |
US20080217217A1 (en) | Device and system for use in imaging particulate matter | |
US20070263212A1 (en) | Non-Hazardous Bulk Material Analyzer System | |
WO1997014950A1 (en) | Method and apparatus for sizing particulate material | |
Krzysiak et al. | Effect of sieve drum inclination angle on wheat grain cleaning in a novel rotary cleaning device | |
JP4402915B2 (en) | Grain sorting device | |
AU2002310397A1 (en) | A control feedback system and method for bulk material industrial processes using automated object or particle analysis | |
WO1985004249A1 (en) | Method for measuring size distribution | |
EP0094741A2 (en) | Differential rate screening | |
JPH0216432A (en) | Aggregate grading analyzing method and broken stone grading control method for asphalt plant using image processing | |
US4207001A (en) | Particle size analyzer | |
Maerz et al. | Online fragmentation analysis for grinding and crushing control | |
JP6706514B2 (en) | Surface water control method for construction materials | |
KR102209627B1 (en) | Real-time gradation combination system in process of producing aggregate and mixing method using that | |
US20240024891A1 (en) | Rock processing system with at least two value grain grading curves and automated operation dependent on the grading curve discharges | |
GB2034027A (en) | Measurement of the Brightness of Milled Products | |
Rauch et al. | Rapid Test to Establish Grading of Unbound Aggregate Products: Evaluation of Potential Aggregate Grading Technologies | |
JPH03180410A (en) | Method for controlling bulky and powdery charging materials in vertical type furnace | |
Buchanan et al. | Automated Aggregate Grading Analysis: Development and Use | |
CN114729832A (en) | Device and method for producing livestock feed |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
AK | Designated states |
Kind code of ref document: A2 Designated state(s): AE AG AL AM AT AU AZ BA BB BG BR BY BZ CA CH CN CO CR CU CZ DE DK DM DZ EC EE ES FI GB GD GE GH GM HR HU ID IL IN IS JP KE KG KP KR KZ LC LK LR LS LT LU LV MA MD MG MK MN MW MX MZ NO NZ OM PH PL PT RO RU SD SE SG SI SK SL TJ TM TN TR TT TZ UA UG UZ VN YU ZA ZM ZW |
|
AL | Designated countries for regional patents |
Kind code of ref document: A2 Designated state(s): GH GM KE LS MW MZ SD SL SZ TZ UG ZM ZW AM AZ BY KG KZ MD RU TJ TM AT BE CH CY DE DK ES FI FR GB GR IE IT LU MC NL PT SE TR BF BJ CF CG CI CM GA GN GQ GW ML MR NE SN TD TG |
|
121 | Ep: the epo has been informed by wipo that ep was designated in this application | ||
DFPE | Request for preliminary examination filed prior to expiration of 19th month from priority date (pct application filed before 20040101) | ||
WWE | Wipo information: entry into national phase |
Ref document number: 2002310397 Country of ref document: AU |
|
WWE | Wipo information: entry into national phase |
Ref document number: 028101685 Country of ref document: CN |
|
WWE | Wipo information: entry into national phase |
Ref document number: 529760 Country of ref document: NZ |
|
WWE | Wipo information: entry into national phase |
Ref document number: 2002737470 Country of ref document: EP |
|
WWP | Wipo information: published in national office |
Ref document number: 2002737470 Country of ref document: EP |
|
REG | Reference to national code |
Ref country code: DE Ref legal event code: 8642 |
|
WWW | Wipo information: withdrawn in national office |
Ref document number: 2002737470 Country of ref document: EP |
|
NENP | Non-entry into the national phase |
Ref country code: JP |
|
WWW | Wipo information: withdrawn in national office |
Country of ref document: JP |